If you’ve tried to source analyst price target data — full history, accuracy-scored, machine-readable — you already know the options aren’t good.
Bloomberg and FactSet charge $20,000+ a year. Public aggregators give you today’s consensus but strip the history. And almost nobody includes the part that actually matters: whose price targets actually got reached.
Here’s what this post covers: how AnaChart’s full database of 833,000+ analyst price target events is now available for direct access — as a warehouse-native Snowflake or BigQuery share starting at $1,000/month, or as a one-time custom report from $149 with no account required.
Want to see the data before reading further? A free AAPL sample — full analyst coverage, price targets, ratings, and accuracy scores for Apple — is available at anachart.store. No sign-up. No commitment.
In this post:
- What is analyst price target data?
- What’s inside the AnaChart database
- Two ways to access the data
- Who uses analyst price target data — and how
- How the accuracy scores are calculated
- Frequently asked questions
- How to get started
What is analyst price target data?
Analyst price target data is the structured record of every price target and rating issued by Wall Street sell-side analysts — including the date of issuance, the target price, the rating, and critically, whether the target was subsequently hit.
Most sources only give you the current consensus: today’s average target across all analysts covering a stock. That’s useful, but it hides the most important variable — analyst skill.
AnaChart’s analyst price target data goes further. Every target is scored against the stock’s realised price over the evaluation horizon. The result is a hit rate for each analyst: the percentage of their targets that came true, measured across every forecast they’ve ever made.
That’s the difference between knowing what Wall Street said and knowing whose targets actually got reached.
| Stock | Analysts covering | Avg price target | Met ratio | Avg days to hit |
|---|---|---|---|---|
| QCOM | 19 | $209.03 | 92.87% | 525 |
| NVDA | 38 | $298.20 | 80.13% | 144 |
| VZ | 13 | $49.54 | 57.72% | 802 |
What’s inside the AnaChart database
The database covers 7,191 Wall Street analysts across 9,686 stocks, with records going back over 20 years.
Here’s what each record contains:
- Analyst name, firm, and date of each price target issuance or revision
- Target price and rating (Buy / Hold / Sell / equivalent) at time of issue
- Subsequent realised price, evaluated against the target at the standard horizon
- Cumulative hit rate and accuracy score for the analyst across all historical forecasts
Total events: 833,000+ analyst price target records.
That last bullet — the accuracy score — is what no other analyst data provider offers at this depth. Bloomberg has raw revision history; it doesn’t score it. FactSet aggregates consensus; it doesn’t rank analysts by skill. AnaChart does.
The over 20-years depth isn’t a marketing number. It reflects the actual span of price target and outcome records built from verified historical sources. For most accuracy models, over 20 years makes individual analyst hit rates statistically meaningful — even for analysts who cover a narrow set of stocks.
Two ways to access the data
AnaChart offers two delivery paths. Which one fits depends on whether you have an existing data stack or just need a specific cut of the data.
| Warehouse Share | Custom Report | |
|---|---|---|
| Delivery | Snowflake or BigQuery native share | Excel or PDF |
| Setup required | Existing warehouse account | None |
| Third-party sign-up | Snowflake or BigQuery account | Not required |
| Turnaround | Live within 5 business days | 24–48 hours (same-day target) |
| Price | From $1,000/month | From $149 one-time |
| Coverage | NASDAQ 100 to full market | Any ticker, analyst, or firm |
| Commitment | Monthly subscription | None — pay per query |
| Best for | Ongoing models, quant teams, institutional data stacks | One-time studies, IR briefs, research |
| Free sample | AAPL (no sign-up) | — |
Bottom line: if analyst accuracy data needs to feed a live model or systematic process, the warehouse share is the right path. If you need a specific slice of the data — one analyst’s history, one stock’s coverage, one sector comparison — the custom report gets you there without any infrastructure commitment.
Warehouse-native delivery: Snowflake or BigQuery
For teams with an existing data stack, AnaChart delivers the full dataset as a native share directly into your Snowflake or BigQuery environment.
No ETL to configure. No proprietary API to learn. No file format to parse. The share appears in your warehouse and joins to your existing models like any internal table.
This is the access path behind AnaChart Corporate Access — built for portfolio managers, quant analysts, and data teams at institutional firms who need analyst accuracy data as a standard model input, not a lookup tool.
Coverage tiers start from the NASDAQ 100 and scale to full market coverage. A free sample (AAPL, schema documentation included) is available at anachart.store with no sign-up required, so a data team can verify fit before committing.
What institutional clients use the warehouse feed for:
- Accuracy-weighted consensus models. Instead of averaging price targets equally, weight each target by the analyst’s historical hit rate. A 10-year, 80%-accuracy analyst carries more signal than a first-year analyst with no track record. Standard consensus treats both equally — AnaChart data lets you fix that.
- Analyst selection. Screen for analysts who have a demonstrably above-average hit rate on a specific sector or ticker before deciding whose coverage to follow or pay for.
- Firm benchmarking. Compare the accuracy distribution across sell-side firms. Useful for buy-side teams evaluating broker relationships, and for IR teams assessing which analysts covering their stock are historically credible.
- Backtesting signals. Use historical price target revisions as a factor input in systematic strategies. The AnaChart accuracy score functions as a quality filter — removing low-skill analyst noise before the signal enters a model.
Custom data reports: from $149, no warehouse required
Not every use case needs a Snowflake integration.
Research teams, independent analysts, IR professionals, and individual investors sometimes need one specific cut of the data — a single analyst’s full history, all targets on a given ticker over five years, an accuracy comparison across a broker’s coverage team, or a bespoke dataset for a one-time study.
AnaChart’s Custom Data Reports service handles exactly that.
Here’s how it works: submit a plain-English description of what you need — ticker, analyst, firm, timeframe, output format. AnaChart queries the database directly and delivers the results as Excel or PDF.
No Snowflake account. No BigQuery marketplace sign-up. No third-party onboarding of any kind.
Reports are fulfilled within 24–48 hours, with same-day turnaround the standard target. Pricing starts at $149 for a single query and scales to $999 for complex multi-variable reports.
Common requests:
- Full price target history and hit rate for a named analyst (useful before meetings with sell-side coverage)
- All analysts who have covered a specific ticker, ranked by accuracy, over the past 10 years
- Head-to-head accuracy comparison between two or more sell-side firms on a given sector
- All analyst upgrades and downgrades on a stock in a defined date range, with outcome scores appended
- Analyst coverage breadth and accuracy profile for a corporate IR briefing
Who uses analyst price target data — and how
Buy-side portfolio managers weight consensus by each analyst’s track record instead of treating every name equally — a over 20-years hit rate per analyst, built straight into the investment process.
Quantitative analysts and data teams integrate the Snowflake or BigQuery share directly into existing factor models. Analyst revision signals are a well-established factor in systematic equity strategies; AnaChart accuracy scores add a quality dimension that raw revision data does not provide.
Corporate IR teams use the database to understand which analysts covering their stock have a historically strong track record. In investor communications, citing that the analysts with the strongest track records covering the company are bullish is a more defensible position than citing the consensus alone.
Individual investors with a research process cross-reference the top analyst rankings on anachart.com before acting on a rating, and commission custom reports for deeper dives into specific analyst-stock relationships.
Financial journalists and research contributors reference AnaChart accuracy data to contextualise analyst commentary — noting not just what an analyst said, but their historical hit rate on the stock or sector in question.
How the accuracy scores are calculated
Every analyst’s accuracy score is calculated against realised end-of-day prices over the standard evaluation horizon. A target counts as a hit if the stock reached the target price within the horizon from the date of issuance.
The methodology is consistent across all 7,191 analysts in the database and is documented in full on the AnaChart methodology page.
One note worth making: most institutional data providers either don’t score analyst accuracy at all, or cover a rolling 12–36 month window. A over 20-years baseline allows hit rates to be statistically meaningful even for analysts who cover a relatively narrow set of stocks — the sample size is large enough to distinguish skill from luck. Independent bodies such as the CFA Institute have long documented systematic bias in sell-side forecasts — which is why an outcome-scored dataset, not raw consensus, is the input that actually carries signal.
Frequently asked questions
What is analyst price target data?
Analyst price target data is the structured record of every price target and rating issued by Wall Street sell-side analysts, including the date, target price, rating, and whether the target was subsequently realised. AnaChart’s database covers 833,000+ events across 7,191 analysts and 9,686 stocks, with over 20 years of history and an accuracy score for every analyst.
How do I get historical analyst price target data?
AnaChart offers two access paths. Teams with a Snowflake or BigQuery environment can receive a warehouse-native share from $1,000/month. Teams without a warehouse account can request a custom one-time report from $149 — submit a plain-English description of what you need, and AnaChart delivers Excel or PDF within 24–48 hours. A free AAPL sample is available at anachart.store with no sign-up required.
Does AnaChart’s analyst data include accuracy scores?
Yes — and this is what separates AnaChart from every other analyst data source. Every price target in the database is evaluated against the stock’s realised price and assigned a hit/miss outcome. Each analyst has a cumulative hit rate across all their historical forecasts. For example, Mizuho’s Vijay Rakesh has reached 54 of his last 55 QCOM price targets — a 98% met ratio that a simple consensus average never surfaces. Bloomberg and FactSet have raw revision history but do not score it.
What is the difference between a Snowflake data share and a custom report?
A Snowflake or BigQuery share delivers the full database directly into your existing data warehouse — no ETL, no file transfer, no API. It is a live share that joins to your internal models like any native table. A custom report is a one-time query: you describe what you need, AnaChart runs the query, and you receive the results as Excel or PDF. The custom report path requires no warehouse account or technical setup.
Is the free AAPL sample representative of the full database?
Yes. The AAPL sample includes the same fields, schema, and accuracy scoring that appear in the full warehouse share. It also includes schema documentation. It is intended to allow data teams to verify format and data quality before committing to a subscription. No sign-up or payment details are required to access it.
How far back does AnaChart’s analyst price target history go?
AnaChart’s database goes back over 20 years. This is the actual span of verified price target and outcome records in the system. For most institutional accuracy models, a over 20-years window provides sample sizes large enough to distinguish analyst skill from market-driven noise — even for analysts covering a narrow set of stocks.
How to get started
The fastest way to evaluate the data is the free AAPL sample at anachart.store. It includes full analyst coverage, price targets, ratings, and accuracy scores for Apple — plus schema documentation. No sign-up. No payment details.
For the warehouse share (Snowflake or BigQuery), pricing and coverage tiers are listed on anachart.store. The standard onboarding path is a brief discovery call to confirm coverage scope and delivery format, followed by a live data share within five business days.
For a custom one-time report, submit your query at anachart.store/custom-data-queries. Describe what you need in plain English — ticker, analyst, firm, date range, format — and the team will confirm scope and turnaround before billing. No minimum commitment. Pay per query.
Note: This post covers institutional and professional data access via anachart.store. For retail investor access to analyst accuracy rankings, visit anachart.com.
Last updated: 14 July 2026
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Keep reading
- Analyst accuracy data: the met-ratio and track-record field, with a real per-analyst example.
- The Snowflake and BigQuery feed: how the native share reaches your warehouse and joins to your models.
- Are analyst price targets a lagging indicator?: the 0.705 correlation between a revision and the move the stock had already made, and what it does to a revision signal.
- The analyst ID problem in price target data: why 7,748 vendor identifiers resolve to 7,191 people, and how a broken join key quietly breaks a backtest.